Advanced Internet of Things for Smart Cyber-Physical Infrastructure Systems

Submission Deadline:  20 March 2021

IEEE Access invites manuscript submissions in the area of Advanced Internet of Things for Smart Cyber-Physical Infrastructure Systems.

The Internet of Things (IoT) is rapidly gaining ground as a priority, multidisciplinary research topic in many
academic and industrial disciplines, especially in Cyber-Physical infrastructures, such as renewable
energy generation, smart vehicle management, and water quality monitoring. Due to the rapid
proliferation of smart sensors and meters, wearable devices and smartphones, the Internet of Things-
enabled technology is evolving infrastructure from conventional operation and maintenance business
models to more efficient, sustainable, smart and resilient systems. The successful utilization of IoT
enabled technology in Cyber Physical Infrastructure Systems (CPIS) will enable them to be faster and
more proactive, have a lower overall cost, provide improved business practices and enhance
sustainability. Future IoT enabled infrastructures will be realized to provide timely information
communication and effective decision-making for intelligent society and industry.

There are already IoT smart applications used without human intervention in areas such as traffic
congestion monitoring, household waste recycling, water consumption monitoring and alert systems in
cities. People will play a major role as they generate and use the data coming from these devices. IoT
technology provides potential for optimal feedback and decisions on various infrastructure needs, where it
enables seamless alignments of the local providers with the global potential of wider communities. It
leads to new smart services and increases the efficiency for infrastructure.

However, empowering the utility of IoT enabled technology in Cyber-Physical infrastructure is still
significantly challenging, considering the shortage of cost-effective and accurate smart sensors and
meters, unstandardized IoT system architectures, heterogeneity of connected wearable devices,
multidimensionality and high volume of data generated, and the high demand for interoperability.

From a
user-centric perspective, the successful use of IoT in infrastructure will also need an interoperable IoT
environment for delivery and research, tightly-coupled data mining applications, adequate data and
knowledge standards of self-empowerment, and a sound decision-making foundation. Research will focus
on designing and developing more connected complex systems, dealing with the current lack of
standards, and figuring out ways to analyze the deluge of data. Complexity will be an important factor to
study and control: The behavior of every single node in IoT will need to be considered to determine its
potential impact on the whole CPIS. These challenges and needs provide a lot of opportunities to explore
and investigate new concepts, algorithms and applications in IoT enabled smart infrastructure.

The goal of this Special Section on Internet of Things for smart CPIS is to bring together researchers and
practitioners from both academia and industry into a forum, and to show the state-of-the-art research and applications in utilizing IoT enabled technology for cyber-physical infrastructure, by presenting efficient
scientific and engineering solutions, addressing the needs and challenges for integration with new
technologies, and providing visions for future research and development.

The central theme of the proposed Special Section is on advanced internet of things technologies for
smart cyber-physical infrastructure systems, where smart sensing technologies, IoT architectures,
services, applications, and data analytics for infrastructure applications are the focus areas, and broad
aspects and issues will be well discussed.

This topic should be of great interest to IEEE Access readers.
The theme of the Special Section (SI) is especially focused on the three major aspects of IoT for
infrastructure: (1) intelligent monitoring with increased security and validity in CPS by using a variety of
IoT assets or technologies, including sensors, devices and mobile applications, (2) Interoperability and
data sharing services across IoT infrastructures supporting heterogeneous elements to cooperate
seamlessly to share information, and (3) Creation of ecosystems of “Platforms for Connected Smart
Objects”; integrating the future generations of smart devices (i.e. sensors) and network technologies and
other evolving ICT advances.

The Special Section aims to provide a forum for experts to disseminate their recent advances and views
on future perspectives in the field. The Special Section aims to publish original, significant and visionary
articles which present ideas, innovations, and applications of utilizing IoT enabled technology for
improving the efficiency, sustainability and reliability of infrastructure.

The topics of interest include, but are not limited to:

  • Intelligent sensing and monitoring techniques and applications for CPIS
  • Challenges and issues of intelligent sensing and data collection techniques in CPIS
  • Integrated communication and distributed computing design for CPIS
  • Internet of Things architecture design for CPIS
  • Theoretical computing foundation and models for CPIS
  • Intelligent real time data analytics for CPIS
  • Security and privacy issues in the distributed computing infrastructure of CPIS
  • Machine learning techniques for CPIS
  • Co-design of distributed computing and physical systems in CPIS
  • Large-scale data analysis in CPIS
  • Scalable data and resource management in CPIS
  • Robotics and autonomous systems for CPS
  • Human in the loop robotics and interaction tech for CPS
  • Innovative and cutting-edge technologies for CPIS
  • Applications of Cyber-physical system

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

 Associate Editor:  Po Yang, Sheffield University, UK

 
 Guest Editors:

    1. Wenyan Wu, Birmingham City University, UK
    2. Zofia Lukzos, Delft University of Technology, Netherlands
    3. Zahid Akhtar, State University of New York Polytechnic Institute, USA

 

Relevant IEEE Access Special Sections:

  1. Big Data Technology and Applications in Intelligent Transportation
  2. Innovation and Application of Internet of Things and Emerging Technologies in Smart Sensing
  3. Emerging Trends, Issues and Challenges for Array Signal Processing and Its Applications in Smart City

 

IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

 Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

 For inquiries regarding this Special Section, please contact: po.yang@sheffield.ac.uk.

Advanced Artificial Intelligence Technologies for Smart Manufacturing

Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of Advanced Artificial Intelligence Technologies for Smart Manufacturing.

As the world enters a new phase of industrialization (Industry 4.0, or the fourth industrial revolution), smart manufacturing has become crucial. Industry 4.0 refers to an industrial transformation aided by smart manufacturing and data exchange, such as high-level factory automation and Internet of Things applications. Artificial intelligence and smart machinery have also become integral research areas in manipulation. Researchers from academia and various industries are now working to develop the next generation of intelligent smart manufacturing applications. With the application of advanced artificial intelligence technologies, the revolution of the smart manufacturing industry can beadvanced more quickly.

To build a competitive advantage, keep up with the “Industry 4.0” trend, and to attract and filter high quality academic contributions, we have organized this Special Section in IEEE Access on “Advanced Artificial Intelligence Technologies for Smart Manufacturing.” High quality articles within the field are highly encouraged and considered in this Special Section.

The topics of interest include, but are not limited to:

  • Artificial Intelligence, Embedded Systems and Cloud Computing in Manufacturing
  • Smart Actuators and Adaptive Control of Machine Tools
  • Man-machine interface and integration
  • Intelligent machinery equipment
  • Intelligent Automation
  • Intelligent manufacturing
  • Advanced signal processing and machine perception of mechanical systems
  • Machine learning techniques for smart manufacturing
  • M2M technology
  • Big Data Analytics in Manufacturing

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

Associate Editor: Her-terng Yau, National Chin-Yi University of Technology, Taiwan

Guest Editors:

    1. Stephen D. Prior, University of Southampton, UK
    2. Yang Wang, Georgia Institute of Technology, USA
    3. Yunhua Li, BeiHang University, China

 

Relevant IEEE Access Special Sections:

  1. Artificial Intelligence Technologies for Electric Power Systems
  2. Big Data Technology and Applications in Intelligent Transportation
  3. Advances in Machine Learning and Cognitive Computing for Industry Applications

 

IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: pan1012@ms52.hinet.net; htyau@ncut.edu.tw.

Recent Advances on Hybrid Complex Networks: Analysis and Control

Submission Deadline: 31 October 2020

IEEE Access invites manuscript submissions in the area of Recent Advances on Hybrid Complex Networks: Analysis and Control.

Due to varied complexities such as network dynamics complexity, statistical complexity and so on, some complex networks involve more than one discipline. Among network dynamics, both  impulsive effects and logical dynamics have attracted increasing attention recently. It is of interest and importance to study the complex networks with impulsive effects and logical dynamics. Note that these networks are called hybrid complex networks, which widely exist in cells, ecology, social systems and communication engineering.

In hybrid complex networks, many nodes are coupled together through networks, and their properties lead to very complex dynamic behaviors, including discrete and continuous dynamic behaviors, with both the time and state space taking finite values. The continuous parts of systems are often described by differential equations, while the discrete parts can be described by difference equations. The logical networks are usually used to model the systems where time and state space take finite values. Although interesting work has been reported on hybrid complex networks, there is some conservativeness on both the analysis method and relevant results. To be specific, conservative impulsive delay inequalities were used in some literatures and corresponding stability or synchronization criteria seem hard to check. Therefore, it is necessary to find effective approaches to break some conservativeness on both the analysis method and relevant results of hybrid complex networks.

Our proposed Special Section will provide a valuable and timely platform for the exchange of the latest advances in hybrid complex networks.

The topics of interest include, but are not limited to:

  • Analysis of hybrid complex networks: stability/ synchronization/ consensus/ robustness/ complexity analysis/ controllability/ observability/ nonsingularity
  • Synthesis of hybrid complex networks: stabilization/ disturbances decoupling problem/ functions perturbations/ attacks/ optimization

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

Associate Editor:  Jianquan Lu, Southeast University, China

Guest Editors:

    1. Daniel W. C. Ho, City University of Hong Kong, Hong Kong, China
    2. Tingwen Huang, Texas A&M University, Qatar
    3. Jürgen Kurths, Potsdam Institute for Climate Impact Research, Germany
    4. Ljiljana Trajkovic, Simon Fraser University, Canada

 

Relevant IEEE Access Special Sections:

  1. Complex Networks Analysis and Engineering in 5G and beyond towards 6G
  2. Body Area Networks
  3. Internet-of-Things Attacks and Defenses: Recent Advances and Challenges


IEEE Access Editor-in-Chief:
  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: jqluma@seu.edu.cn.

Artificial Intelligence in CyberSecurity

Submission Deadline: 30 July 2019

IEEE Access invites manuscript submissions in the area of Artificial Intelligence in CyberSecurity.

Recent studies show that Artificial Intelligence (AI) has resulted in advances in many scientific and technological fields, i.e., AI-based medicine, AI-based transportation, and AI-based finance. It can be imagined that the era of AI will be coming to us soon. The Internet has become the largest man-made system in human history, which has a great impact on people’s daily life and work. Security is one of the most significant concerns in the development of a sustainable, resilient and prosperous Internet ecosystem. Cyber security faces many challenging issues, such as intrusion detection, privacy protection, proactive defense, anomalous behaviors, advanced threat detection and so on. What’s more, many threat variations emerge and spread continuously. Therefore, AI-assisted, self-adaptable approaches are expected to deal with these security issues. Joint consideration of the interweaving nature between AI and cyber security is a key factor for driving future secure Internet.

The use of AI in cybersecurity creates new frontiers for security research. Specifically, the AI analytic tools, i.e., reinforcement learning, big data, machine learning and game theory, make learning increasingly important for real-time analysis and decision making for quick reactions to security attacks. On the other hand, AI technology itself also brings some security issues that need to be solved. For example, data mining and machine learning create a wealth of privacy issues due to the abundance and accessibility of data. AI-based cyber security has a great impact on different industrial applications if applied in appropriate ways, such as self-driving security, secure vehicular networks, industrial control security, smart grid security, etc. This Special Section in IEEE Access will focus on AI technologies in cybersecurity and related issues. We also welcome research on AI-related theory analysis for security and privacy.

The topics of interest include, but are not limited to:

  • Reinforcement learning for cybersecurity
  • Machine learning for proactive defense
  • Big data analytics for security
  • Big data anonymization
  • Big data-based hacking incident forecasting
  • Big data analytics for secure network management
  • AI-based intrusion detection and prevention
  • AI approaches to trust and reputation
  • AI-based anomalous behavior detection
  • AI-based privacy protection
  • AI for self-driving security
  • AI for IoT security
  • AI for industrial control security
  • AI for smart grid security
  • AI for security in innovative networking
  • AI security applications

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:   Chi-Yuan Chen, National Ilan University, Taiwan

Guest Editors:

  1. Wei Quan, Beijing Jiaotong University, China
  2. Nan Cheng, University of Toronto, Canada
  3. Shui Yu, Deakin University, Australia
  4. Jong-Hyouk Lee, Sangmyung University, Republic of Korea
  5. Gregorio Martinez Perez, University of Murcia (UMU), Spain
  6. Hongke Zhang, Beijing Jiaotong University, China
  7. Shiuhpyng Shieh, National Chiao Tung University, Taiwan

 

Relevant IEEE Access Special Sections:

  1. Artificial Intelligence and Cognitive Computing for Communications and Networks
  2. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things
  3. Cyber-Physical Systems


IEEE Access Editor-in-Chief:
  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: chiyuan.chen@ieee.org.

Deep Learning: Security and Forensics Research Advances and Challenges

Submission Deadline: 30 October 2019

IEEE Access invites manuscript submissions in the area of Deep Learning: Security and Forensics Research Advances and Challenges.

Generative and discriminative deep learning models have been utilized in a broad range of artificial intelligence-related applications (e.g., computer vision, natural language processing), cybersecurity (e.g., facial authentication, and vulnerability and exploitation detection), and forensic-related tasks. However, cyber attackers could breach the trustworthiness and efficiency of deep learning models (i.e., adversarial machine/deep learning). There are different methods that have been used to hack machine/deep learning models, for example, exploiting the model structure, injecting malicious data in the training, validation, and/or testing sets, and/or modifying hyper-parameters of the models.

The objective of this Special Section in IEEE Access is to compile recent research efforts dedicated to the study of Deep Learning in security and forensic-related applications, to enhance performance in biometrics, spoofing detection, intrusion detection, authentication, digital forensics, access control, image steganography and steganalysis, deep learning computation and training security, and malicious web content identification, etc. Specifically, we are soliciting for high quality and unpublished work on recent advances in new deep learning methodologies that can be applied to a broad range of applications.

The topics of interest include, but are not limited to:

  • Adversarial attacks in deep learning
  • Cryptography protocols and algorithms for deep learning
  • Deep learning computation and training security
  • Deep learning for cyber security applications (e.g., malicious web content identification, intrusion detection and privacy-preserving, vulnerability and exploitation Identification, and facial and/or biometric spoofing detection)
  • Deep learning for natural language processing
  • Deep learning for video and image processing
  • Deep learning-based forensics and anti-forensics
  • Gait authentication and deep learning
  • Generative adversarial deep learning
  • Object detection and transfer learning
  • Privacy and trust challenges associated with deep learning
  • Trends in specific deep learning domains

 

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Kim-Kwang Raymond Choo, University of Texas at San Antonio, USA

Guest Editors:

  1. Zhen Qin, University of Electronic Science and Technology of China, China
  2. Nour Moustafa, University of New South Wales @ADFA, Australia
  3. William Bradley Glisson, Sam Houston State University, USA
  4. Sheikh Mahbub Habib, Continental AG, Germany

 

Relevant IEEE Access Special Sections:

  1. Advanced Software and Data Engineering for Secure Societies
  2. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things
  3. Trusted Computing


IEEE Access Editor-in-Chief:
  Derek Abbott, Professor, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: raymond.choo@fulbrightmail.org.

Mobile Service Computing with Internet of Things

Submission Deadline: 31 March 2019

IEEE Access invites manuscript submissions in the area of Mobile Service Computing with Internet of Things.

Service computing is a bridge among systems, man, and cybernetics, which covers the science and technology of connecting the gap between business and IT services, and has attracted increasing attention from both industry and academia. The services of IoT are defined as software artifacts that are autonomous, self-described, reusable, and highly portable. They’re the basic units for building rapid, low-cost, secure, and reliable applications. Thus, the service computing paradigm saves on development costs that would otherwise be spent creating new software components for each new business process.

Due to the rapid developments in mobile devices and wireless technologies, mobile devices play an increasingly important role in our daily lives. Thus, there is great potential in mobile technology   and many opportunities for traditional service computing in the mobile environment. Services are no longer limited to traditional contexts and platforms. They can be deployed on mobile devices or cloud servers and delivered over wireless networks. Mobile service computing is undoubtedly enabling us to provide and access services anytime and anywhere, which greatly facilitates our life, work, and studies. However, the application of mobile service computing still faces challenges due to key limitations such as constant mobility, limited capability, restricted power, unguaranteed security, etc., which bring great challenges for both service provision and consumption.

The goals of this Special Section in IEEE Access are (1) to present the state-of-the-art research on mobile service computing with IoT, and (2) to provide a forum for experts to disseminate their recent advances and views on future perspectives in the field.

In this Special Section, we invite articles that present new theories, methods and techniques applied to mobile service computing. We particularly encourage articles demonstrating novel strategies to new types of mobile service computing domains such as mobile cloud computing, mobile edge computing, etc.  Applications may be drawn by investigating the usage of novel methods for all aspects of the mobile service computing system, including system design, performance optimization, algorithm design, scheduling methods, energy saving, and security management.

The topics of interest include, but are not limited to:

  • Service description in mobile environments for IoT
  • Performance optimization in mobile environment
  • Quality evaluation for mobile services of IoT
  • Mobile service selection, recommendation and composition
  • Mobile service provisioning
  • Energy efficiency in mobile service computing
  • Mobile service offloading
  • Smart Technologies for mobile service computing
  • Formal Modeling and Verification for mobile service computing
  • Big data and data analysis for mobile service computing
  • Resource management in mobile service environments
  • Security and privacy in mobile service computing
  • Mobile device management (configuration, performance, and capacity)
  • Mobile network and communication services in IoT

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Tie Qiu, Tianjin University, China


Guest Editors:

  1. Shuiguang Deng, Zhejiang University, China
  2. Wenbing Zhao, Cleveland State University, USA
  3. Javid Taheri, The University of Sydney, Australia
  4. Weiming Shen, University of Western Ontario, Canada

 

Relevant IEEE Access Special Sections:

  1. Emotion-aware Mobile Computing
  2. Recent Advances in Socially-aware Mobile Networking
  3. Emergent Topics for Mobile and Ubiquitous Systems in Smartphone, IoT, and Cloud Computing Era


IEEE Access Editor-in-Chief:
Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: qiutie@ieee.org

 

Advanced Software and Data Engineering for Secure Societies

Submission Deadline: 30 June 2019

IEEE Access invites manuscript submissions in the area of Advanced Software and Data Engineering for Secure Societies.

Advances in Information and Communication Technologies (ICT) have remodeled the way we live and work over the last few years. The use of mobile Internet technology is already widespread, with more than 1.1 billion people constantly connected to the digital world using smartphones and tablets. The digital world expands its frontiers every day to include not only systems and humans, but also physical objects. Machinery, shipments, infrastructures, and devices are being equipped with networked sensors and actuators that enable them to monitor their environment, report their status, receive instructions, and even collaborate to take appropriate actions. Social media platforms such as Facebook, Twitter, WhatsApp, etc., are progressively becoming the norm rather than exception as to the way through which people meet, socialize, communicate and work.

While such technologies promise to make our lives easier, they raise significant security challenges for modern societies. They can be misused by malicious individuals or groups to harm people or disrupt systems and services at unprecedented scale. For example, terrorist groups and organizations try to exploit popular social media to influence vulnerable people and drive them to commit terrorist attacks. In a recent denial of service attack, control was taken of millions of unsecured internet routers around the globe to flood a major DNS provider, leading to global internet outages. Hackers try repeatedly to compromise the information systems of many democratic organizations around the globe to release information about candidates and sway the opinions of voters.

The goal of this Special Section in IEEE Access is to collect recent advances, innovations and practices in software, data and knowledge engineering for building security systems, techniques and solutions with the objective of protecting our citizens, society and economy as well as our infrastructures and services, our prosperity, political stability and well-being.

The topics of interest include, but are not limited to:

  • Forensic-ready software and system engineering
  • Software architectures for fighting online radicalization, extremism and terrorism
  • Software architectures for fighting the dissemination of fake news
  • Data mining and machine learning applied to cyber security
  • Data protection in the digital space
  • Privacy protection in the cyber-physical-social space
  • Software and data architectures for the protection of critical infrastructures
  • Software and data architectures for community policing
  • Robust machine learning
  • Identification of adversarial examples
  • Protection of systems against adversarial attacks
  • Transparency for security
  • Human factors for secure software systems

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Mahmoud Barhamgi, Claude Bernard Lyon 1 University, France


Guest Editors:

  1. Raúl Lara-Cabrera, Autonomous University of Madrid, Spain
  2. Nobukazu Yoshioka, National Institute of Informatics, Japan
  3. Xiangliang Zhang, King Abdullah University of Science and Technology, Saudi Arabia
  4. Michael N. Huhns, University of South Carolina, USA
  5. Hoda Al Khzaimi, Center of Cyber Security, University of New York Abu Dhabi NYUAD, UAE

 

Relevant IEEE Access Special Sections:

  1. Challenges and Opportunities of Big Data Against Cyber Crime
  2. Cyber-Threats and Countermeasures in the Healthcare Sector
  3. Security Analytics and Intelligence for Cyber Physical Systems


IEEE Access Editor-in-Chief:
Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact:  mahmoud.barhamgi@univ-lyon1.fr

 

Data Mining and Granular Computing in Big Data and Knowledge Processing

Submission Deadline: 30 September 2018

IEEE Access invites manuscript submissions in the area of  Data Mining and Granular Computing in Big Data and Knowledge Processing.

Researchers continue to encounter an explosive growth in big data with high volume, variety, velocity, veracity and value. The “Five Vs” are the key features of big data, and also the causes of inherent uncertainties in the representation, processing, and analysis of big data. Data is continuously recorded in a fast sampling rate and is leading to an explosion of data volume which calls for a specific strategy to increase scalability of a computational method. Installation of various sensors make it possible for numerous variables to be captured. This issue not only results in exponential growth of data volume but also generates heterogeneous data samples of various types: images, videos, texts, sounds, etc. The benefits from the management of big data are clear: the larger the data, the higher the degree of knowledge that can be extracted from it. Therefore, data mining becomes an essential technique to process big data. Moreover, real-life big data is now available everywhere from the Internet, sensor networks, social networks, and proprietary databases. The big data mining remains an open issue for both academia and practitioners because of the issue of uncertainty caused by inaccurate measurement, faulty sensors, missing values, etc.

In the past few years, a great number of challenging problems have emerged, such as the problem of imbalanced data, multi-label and multi-instance problems, low quality and/or noisy data or semi-supervised learning, among others. In the realm of big data itself, research on big data processing still attracts a growing research interest where the main objective is to set up a scalable big data processing environment which allows one to perform efficient data collection, storage and analytics in an integrated manner.  Parallelization is among the most widely applied technique to handle big data. Instead of relying on a single node, it utilizes a distributed computational framework which makes possible for information to be segregated into a number of computational nodes and to be executed in parallel, thereby increasing scalability of big data processing and memory management of big data.  The Map Reduce, Apache Spark, Flink, etc. are some popular examples of big data analytics which adopt a parallelization scheme.

In the recent past, the evolution of research interest has focused on a relatively new area—granular computing (GrC), based on such technologies as fuzzy sets and rough sets. GrC provides a powerful tool for multiple granularity and multiple-view data analysis. It offers a promising solution to cope with the uncertainty of big data which often contains a significant amount of unstructured, uncertain and imprecise data. GrC can exhibit better capability and advantages in intelligent data analysis, pattern recognition, machine learning and uncertain reasoning for a noticeable amount of data. GrC aims to find a suitable level of granularity of given problems which can be adjusted according to the degree of fuzziness of the given problem. It refers to those advantages, and also challenges, derived from collecting and processing vast amounts of data. There are new challenges regarding the scalability of GrC when addressing very big data.

The exploration of data mining and granular computing in big data and knowledge processing is a multidisciplinary field, which crosses multiple research disciplines and industry domains, including transportation, communications, social network, medical health, and so on.

The goal of this Special Section in IEEE Access is to provide a specific opportunity to review the state-of-the-art of recent data mining and granular computing in big data and knowledge processing, and bringing together researchers in the relevant areas to discuss the latest progress, new research methodologies and potential research topics.

The topics of interest include, but are not limited to:

  • Latest classification algorithms and clustering algorithms for big data processing
  • Supervised/semi-supervised learning method for big data
  • Feature selection/extraction/construction/recognition for big data
  • Data streams and concept drift
  • Data mining in evolutionary computation for real-world applications
  • Large-scale biomedical image mining, assessment and analysis
  • Social network analysis and mining for big data
  • Multi-label/Multi-instance learning in big data and knowledge processing
  • Deep learning and transfer learning for big data analysis
  • Structured spare representation for large-scale image classification
  • Granular soft computing techniques for big data
  • Granular computing theory and application in big data
  • Granular data mining algorithm and application in big data
  • Granular data mining model based MapReduce/Apache Spark
  • Fuzzy granular support vector machines and application in big data
  • Big data analysis for decision-making
  • Multi-criteria knowledge-based systems
  • Evolutionary computation and hybrid systems in big data
  • Cooperation co-evolution for big data
  • Large-scale image and multimedia processing
  • Intelligent adaptive control and analysis in big data applications
  • Multi-agent systems and distributed control of big data
  • Application of data processing technology in large-scale medicine and healthcare data

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Weiping Ding, Nantong University, China


Guest Editors:

  1. Gary G. Yen, Oklahoma State University, USA
  2. Gleb Beliakov, Deakin University, Australia
  3. Isaac Triguero, University of Nottingham, United Kingdom
  4. Mahardhika Pratama, Nanyang Technological University, Singapore
  5. Xiangliang Zhang, King Abdullah University of Science and Technology, Saudi Arabia
  6. Hongjun Li, Nantong University, China


Relevant IEEE Access Special Sections:

 

  1. Recent Computational Methods in Knowledge Engineering and Intelligence Computation
  2. Advanced Big Data Analysis for Vehicular Social Networks
  3. Big Data Analytics in Internet-of-Things and Cyber-Physical System


IEEE Access Editor-in-Chief:
Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: dwp9988@hotmail.com

 

Cyber-Physical Systems

Submission Deadline: 31 December 2018

IEEE Access invites manuscript submissions in the area of  Cyber-Physical Systems.  

Recent years have witnessed the increasing synergy between the computational technologies and physical components. A Cyber-Physical System (CPS) is composed of a collection of devices interacting with each other and communicating with the physical world. It integrates computation and communication aspects together with control and monitoring techniques. Various CPS applications can be found in almost all areas of human life, such as manufacturing systems, smart grids, robotics, transportation systems, medical devices, military, home area networks and smart buildings, etc. 

The aim of this Special Section in IEEE Access is to discuss recent advances of the design, modeling, specification, analysis, verification and application merits of CPS. Such aspects involve interdisciplinary fields of science, thus the following wide range of topics is covered (but not limited to):

Control techniques of CPS:

      • Control systems, concurrent control systems, automatic control and robotics.
      • Distributed and networked control systems.
      • Control algorithms and methodologies.

Design, analysis and verification of CPS:

      • Design methodologies of CPS.
      • Model-based design, including Model-Driven Development, Unified Modeling Language (UML, SysML), etc.
      • Mixed-signal design.
      • Concurrency modeling and analysis, including Petri net-based systems.
      • Optimization techniques.
      • Verification and validation techniques, including formal verification methods.
      • Performance evaluation.
      • Integrated tool suits for CPS design, analysis and verification.

Software and hardware aspects of CPS:

      • Computation models, including mathematical descriptions and models.
      • Cloud computing.
      • Real-time systems, including real-time sensing and computing.
      • Embedded systems.
      • Programmable devices, including logic synthesis and implementation methods.

Networking in CPS:

      • Networked embedded systems.
      • Wireless sensor networks.
      • Internet of things, including aspects of designing, organization and implementation.

Applications of CPS:

      • Autonomous, adaptive and cooperative CPS.
      • Mobile, wearable, and implantable CPS in healthcare.
      • Cognitive CPS with perception, learning, and optimal decision making.
      • Reference architectures for various application domains.
      • Smart grids, power generation and distribution, power systems.
      • Smart cities, home area networks (HANs).
      • Manufacturing, flexible manufacturing systems, smart factories, Industry 4.0.
      • Reconfigurable control systems (including distributed and integrated systems).
      • Dependable CPS (cryptology, security algorithms, security aspects).

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Remigiusz Wisniewski, University of Zielona Gora, Poland

Guest Editors:

  1. Grzegorz Benysek, University of Zielona Gora, Poland
  2. Luis Gomes, Universidade Nova de Lisboa, Portugal
  3. Dariusz Kania, Silesian University of Technology, Poland
  4. Theodore Simos, University of Peloponnese, Greece
  5. MengChu Zhou, New Jersey Institute of Technology, USA


Relevant IEEE Access Special Sections:

  1. Security Analytics and Intelligence for Cyber Physical Systems
  2. Big Data Analytics in Internet-of-Things And Cyber-Physical System
  3. Data-Driven Monitoring, Fault Diagnosis and Control of Cyber-Physical Systems


IEEE Access Editor-in-Chief:
Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: R.Wisniewski@iee.uz.zgora.pl

Towards Service-Centric Internet of Things (IoT): From Modeling to Practice

Submission Deadline: 31 October 2018

IEEE Access invites manuscript submissions in the area of Towards Service-Centric Internet of Things (IoT): From Modeling to Practice

The Internet of Things (IoT) refers to an emerging paradigm, to seamlessly and ubiquitously integrate a large number of smart things with intra/inter links to the physical and cyber worlds. The sensor enabled communication technologies are connecting billions of things, by efficiently utilizing their locations in the real world. It has brought active participation and tangible creation of benefits to the economy and ultimately the society. As the so-called smart things are extremely diverse and heterogeneous in terms of computing and communication technology and resource capability, there is no stand-alone solution towards realization of service-centric provisioning in IoT. The service domain in IoT environments is also diverse including energy efficiency, computing capability, coordination time, resource harvesting capacity, dimension of things, etc. The growing diversity enforces the necessity to address the most significant issue of technological complexity, for practical enhancement and evaluation of quality of service (QoS) and quality of experience (QoE) for service-oriented use cases in IoT environments.

The literature has vastly contributed towards architecture design for cooperative communication, computing and application-centric development. However, the efforts towards realistic modeling and evaluation of QoS and QoE in IoT environments have not witnessed enough attention in academia and industrial research labs. Although the realistic implementations of IoT environments have been realized in various domains including product engineering, marketing, health, sports, and security, the scalability of these implementations is not guaranteed due to the lack of QoS and QoE evaluation in IoT environments. The R&D towards service-centric technologies in IoT environments will support the mass realization of realistic IoT implementations resulting in effective economic and social benefits. Driven by the enhancement of QoS and QoE for diverse use cases in IoT, new technologies are keen to the rise of spanning different service-centric aspects in IoT environments.

The aim of this Special Section in IEEE Access is to provide opportunities for researchers and practitioners to publish their latest and innovative contributions with new methodologies and modeling techniques towards service-centric IoT framework. Theoretical investigation and prototype implementation-based studies are particularly welcomed, as IEEE Access attracts practical articles discussing new experiments or measurement techniques and interesting solutions to engineering, including negative results. The topics of interest include, but are not limited to:

  • Standardization progress in service-centric IoT
  • Business model driven network services management in service-centric IoT
  • Resource management and scheduling for service-centric IoT
  • Energy and resource efficiency in service-centric IoT
  • Location accuracy enhancements for service-centric IoT
  • Cloud and edge computing for massive service-centric IoT applications
  • New waveforms and frame structures for massive IoT connection
  • High-reliability-low-latency tactile communications for IoT
  • Coverage extension with resource constrained sensors
  • Enhancing privacy, security and trust for service-centric IoT

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Yue Cao, Northumbria University, UK

Guest Editors:

  1. Omprakash Kaiwartya, Northumbria University, UK
  2. Xiaodong Xu, Beijing University of Posts and Telecommunications, China
  3. William Liu, Auckland University of Technology, New Zealand
  4. Jaime Lloret, Polytechnic University of Valencia, Spain
  5. Yuanwei Liu, Queen Mary University of London, UK
  6. Yuan Zhuang, Bluvision Inc., USA

 

Relevant IEEE Access Special Sections:

  1. Intelligent Systems for the Internet of Things
  2. Multimedia Analysis for Internet-of-Things
  3. Cyber-Physical-Social Computing and Networking

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: yue.cao@northumbria.ac.uk